BIHi001-B_MB01 StemCNV check report
StemCNV-check, version: 1.0.0
Sample Overview
Sample Information
QC metrics
Summary
Data QC explanations
⇩
These summary tables are meant to serve as a quick overview of the quality of an hPSC sample. This first table contains QC metrics primarily related to the SNP data quality (affected by both the DNA used and the array run itself), this table will also display values from the reference sample if possible. The second table contains QC metrics related to the potentially problematic CNVs and SNVs identified in only the analysed sample.
Coloring of all fields is based on (usually) two thresholds defined in the config file (under the evaluation_settings section), one for a signalling (yellow) level, and one for a more serious warning (orange) or even critical (red) level. Only certain values are potentially considered critical and are marked by bold text in the table, which values behave like this is also defined in the config.
Sample QC explanations
⇩
This table sums up all variant findings from the analysed sample, which were flagged as critical or reportable.
Note that in contrast to general SNP probes on the array, only those single variants that actually show an alternative allele and affect a protein are considered SNVs by StemCNV-check. Variants that match the genotype of assigned reference sample are never considered critical or reportable.
The following criteria are used to assign SNVs as critical or reportable:
Critical SNVs:
- hotspot-match: SNV matching a known stemcell hotspot mutation (see also SNV hotspot coverage)
Reportable SNVs:
ROI-overlap: SNV overlapping a sample specific regions of interest
hotspot-gene: SNV in a gene with known iPSC hotspots (see also SNV hotspot coverage)
protein-ablation: SNV (likely) fully disrupting protein function (i.e. frameshift, stop gain, stop loss)
For copy number variants (CNVs) the assigned label designation takes into account a minimum Check_Score threshold, overlap with a reference call and certain call filter flags (see below). The defined call label criteria are:
Critical de-novo:
Minimum required Check-Score: 55
Exclusion of calls with any filter among: high_probe_dens, probe_gap, min_size, min_probes, min_density
Match to CNV in reference sample: not allowed
Reportable de-novo:
Minimum required Check-Score: 55
Exclusion of calls with any filter among: min_size, min_probes, min_density
Match to CNV in reference sample: not allowed
de-novo call:
Minimum required Check-Score: 0
Exclusion of calls with any filter among: min_size, min_probes, min_density
Match to CNV in reference sample: not allowed
Reference genotype:
Minimum required Check-Score: 0
Exclusion of calls with any filter among:
Match to CNV in reference sample: required
Excluded call:
Minimum required Check-Score: 0
Exclusion of calls with any filter among:
Match to CNV in reference sample: not allowed
The defined CNV filter flags are:
min_size: CNV call below minimum size (<1000bp)
min_probes: CNV call from <5 probes
min_density: CNV call with <10 probes/Mb
high_probe_dens: Probe density of segment is higher than 99% of the array
probe_gap: Probe coverage of segment has considerable gap (min. 33% depending on probe number - see config)
GenCall
This table displays the direct quality metrics from the GenCall software.
PennCNV
The first table displays quality metrics from the PennCNV algorythm. The second displays CNV call statistcs for only PennCNV
CBS
This table displays CNV call statistcs for only CBS.
Config
Changes from default config:
values_changed:
'config: settings : SNV_analysis : SNP_clustering : max_number_samples':
new_value: 25
old_value: 20
iterable_item_added:
'config: settings : SNV_analysis : SNP_clustering : sample_ids[0]': CCD1112Sk_HFF
'config: settings : SNV_analysis : SNP_clustering : sample_ids[1]': BIHi001-A_MB01
'config: settings : SNV_analysis : SNP_clustering : sample_ids[2]': BIHi001-A_WB03
'config: settings : SNV_analysis : SNP_clustering : sample_ids[3]': BIHi001-A_WB04
'config: settings : SNV_analysis : SNP_clustering : sample_ids[4]': BIHi001-B_MB01
'config: settings : SNV_analysis : SNP_clustering : sample_ids[5]': BIHi001-B_WB04
'config: settings : SNV_analysis : SNP_clustering : sample_ids[6]': SCVI_111
'config: settings : SNV_analysis : SNP_clustering : sample_ids[7]': BIHi005-A_MB02_1
'config: settings : SNV_analysis : SNP_clustering : sample_ids[8]': BIHi005-A_MB02_2
'config: settings : SNV_analysis : SNP_clustering : sample_ids[9]': BIHi005-A_MB02_3
'config: settings : SNV_analysis : SNP_clustering : sample_ids[10]': BIHi005-A_WB02
'config: settings : SNV_analysis : SNP_clustering : sample_ids[11]': BIHi005-A_WB04
'config: settings : SNV_analysis : SNP_clustering : sample_ids[12]': NHDF_lot0000477954
'config: settings : SNV_analysis : SNP_clustering : sample_ids[13]': BIHi250-A_MB01
'config: settings : SNV_analysis : SNP_clustering : sample_ids[14]': BIHi250-A_WB01
'config: settings : SNV_analysis : SNP_clustering : sample_ids[15]': BIHi250-A_WB02
'config: settings : SNV_analysis : SNP_clustering : sample_ids[16]': BIHi250-A_WB01_2
'config: settings : SNV_analysis : SNP_clustering : sample_ids[17]': BIHi250-A_WB03
'config: settings : SNV_analysis : SNP_clustering : sample_ids[18]': KOLF21J
'config: settings : SNV_analysis : SNP_clustering : sample_ids[19]': UCSFi001-A_MB01
'config: settings : SNV_analysis : SNP_clustering : sample_ids[20]': UCSFi001-A_WB01
Complete config used by StemCNV-check:
array_definition:
GSAMD-24v3-hg38:
genome_version: hg38
bpm_manifest_file: ../static-data/GSAMD-24v3-0-EA_20034606_A2.bpm
egt_cluster_file: ../static-data/GSAMD-24v3-0-EA_20034606_A1.egt
csv_manifest_file: ../static-data/GSAMD-24v3-0-EA_20034606_A2.csv
penncnv_GCmodel_file: ../static-data/PennCNV-GCmodel_hg38_GSAMD-v24.gcmodel
array_density_file: ../static-data/density_hg38_GSAMD-v24.bed
array_gaps_file: ../static-data/gaps_hg38_GSAMD-v24.bed
penncnv_pfb_file: ../static-data/PennCNV-PFB_hg38_GSAMD-v24.pfb
raw_data_folder: ../RAW_DATA
data_path: data_reports
log_path: data_reports/logs
evaluation_settings:
CNV_call_labels:
Critical de-novo:
minimum_check_score: 55
not_allowed_vcf_filters:
- high_probe_dens
- probe_gap
- min_size
- min_probes
- min_density
reference_match: no
Reportable de-novo:
minimum_check_score: 55
not_allowed_vcf_filters:
- min_size
- min_probes
- min_density
reference_match: no
de-novo call:
minimum_check_score: 0
not_allowed_vcf_filters:
- min_size
- min_probes
- min_density
reference_match: no
Reference genotype:
minimum_check_score: 0
not_allowed_vcf_filters: ~
reference_match: yes
Excluded call:
minimum_check_score: 0
not_allowed_vcf_filters: ~
reference_match: no
summary_stat_warning_levels:
call_rate:
- 0.99
- 0.99
SNP_pairwise_distance_to_reference:
- 500
- 5000
loss_gain_log2ratio:
- 2
- 4
total_calls_CNV:
- 10
- 50
total_calls_LOH:
- 30
- 75
reportable_calls_CNV:
- 5
- 10
reportable_calls_LOH:
- 5
- 10
critical_calls_CNV:
- 1
- 1
critical_calls_LOH:
- 1
- 1
reportable_SNVs:
- 5
- 10
critical_SNVs:
- 1
- 1
call_count_excl_labels: Excluded call
use_last_level:
- call_rate
- computed_gender
- SNP_pairwise_distance_to_reference
- critical_SNVs
- critical_calls_CNV
- critical_calls_LOH
collate_output:
file_format: xlsx
summary_extra_sampletable_cols: Reference_Sample
cnv_collate_call_selection:
whitelist_call_label: ~
blacklist_call_label: Excluded call
global_settings:
cache_dir: ~/work/.stem-cnv-check
hg19_mehari_transcript_db: ../static-data/mehari-data-txs-GRCh37-ensembl-0.10.3.bin.zst
hg38_mehari_transcript_db: ../static-data/mehari-data-txs-GRCh38-ensembl-0.10.3.bin.zst
dosage_sensitivity_scores: __cache-default__
hg19_genome_fasta: /data/cephfs-1/work/projects/cubit/current/static_data/reference/GRCh37/hs37d5/hs37d5.fa
hg38_genome_fasta: /data/cephfs-1/work/projects/cubit/current/static_data/reference/GRCh38/hs38/hs38.fa
hg19_gtf_file: /data/cephfs-1/work/projects/cubit/current/static_data/annotation/GENCODE/19/GRCh37/gencode.v19.annotation.gtf
hg38_gtf_file: /data/cephfs-1/work/projects/cubit/current/static_data/annotation/GENCODE/33/GRCh38/gencode.v33.annotation.gtf
hg19_genomeInfo_file: ../static-data/UCSC_hg19_chromosome-info.tsv
hg38_genomeInfo_file: ../static-data/UCSC_hg38_chromosome-info.tsv
settings:
CNV.calling.tools:
- PennCNV
- CBS
probe_filter_sets:
standard:
GenTrainScore: 0.15
GenCallScore: 0.15
Position.duplicates: highest-GenCall
Pseudoautosomal: remove-male
default_probe_filter_set: standard
PennCNV:
probe_filter_settings: _default_
enable_LOH_calls: yes
call.merging:
merge.gap.absolute: 500
merge.gap.snps: 10
call.extension.percent: 60
maximum.gap.allowed: 500000
filter.minprobes: 5
filter.minlength: 1000
filter.mindensity.Mb: 10
CBS:
probe_filter_settings: _default_
undo.SD.val: 1
call.merging:
merge.gap.absolute: 500
merge.gap.snps: 10
call.extension.percent: 60
maximum.gap.allowed: 500000
filter.minprobes: 5
filter.minlength: 1000
filter.mindensity.Mb: 10
LRR.loss: -0.25
LRR.loss.large: -1.1
LRR.gain: 0.2
LRR.gain.large: 0.75
LRR.male.XorY.loss: -0.5
LRR.male.XorY.gain: 0.28
LRR.male.XorY.gain.large: 0.75
LRR.female.X.loss: -0.05
LRR.female.XX.loss: -0.9
LRR.female.X.gain: 0.5
LRR.female.X.gain.large: 1.05
array_attribute_summary:
density.windows: 100000
min.gap.size: auto-array
CNV_processing:
call_processing:
probe_filter_settings: _default_
tool.overlap.greatest.call.min.perc: 50
tool.overlap.min.cov.sum.perc: 60
filter.minprobes: 5
filter.minlength: 1000
filter.mindensity.Mb: 10
min.reciprocal.coverage.with.ref: 50
gap_area.uniq_probes.rel:
- -12.0
- 12.5
min.perc.gap_area: 0.33
density.quantile.cutoff: 0.99
gene_overlap:
exclude_gene_type_regex: ~
include_only_these_gene_types:
- lncRNA
- miRNA
- protein_coding
whitelist_hotspot_genes: yes
stemcell_hotspot_list: __inbuilt__/supplemental-files/CNV-stemcell-hotspots.tsv
cancer_gene_list: __inbuilt__/supplemental-files/genelist-cancer-drivers.tsv
dosage_sensitive_gene_name_fixes: __inbuilt__/supplemental-files/gene-names-mapping-dosage-sensitivity.tsv
Check_score_values:
pHaplo_threshold: 0.86
pTriplo_threshold: 0.94
dosage_sensitive_gene: 5
any_other_gene: 0.2
single_copy_factor: 0.333
double_copy_factor: 0.5
neutral_copy_factor: 0.275
flat_decrease: 15
precision_estimation_file: __inbuilt__/supplemental-files/precision_estimates.tsv
SNV_analysis:
probe_filter_settings: _default_
snv_hotspot_table: __inbuilt__/supplemental-files/SNV-stemcell-hotspots.tsv
flag_GenCall_minimum: 0.2
variant_selection:
Impact:
- HIGH
- MODERATE
Annotation_regex: ~
include_all_ROI_overlaps: yes
critical_SNV: hotspot-match
reportable_SNV:
- ROI-overlap
- hotspot-gene
- protein-ablation
protein_ablation_annotations:
Impact: HIGH
Annotation_regex: ~
protein_change_annotations:
Impact: ~
Annotation_regex: missense_variant|inframe
SNP_clustering:
sample_ids:
- CCD1112Sk_HFF
- BIHi001-A_MB01
- BIHi001-A_WB03
- BIHi001-A_WB04
- BIHi001-B_MB01
- BIHi001-B_WB04
- SCVI_111
- BIHi005-A_MB02_1
- BIHi005-A_MB02_2
- BIHi005-A_MB02_3
- BIHi005-A_WB02
- BIHi005-A_WB04
- NHDF_lot0000477954
- BIHi250-A_MB01
- BIHi250-A_WB01
- BIHi250-A_WB02
- BIHi250-A_WB01_2
- BIHi250-A_WB03
- KOLF21J
- UCSFi001-A_MB01
- UCSFi001-A_WB01
id_columns: ~
match_columns:
- Chip_Name
- Sample_Group
max_number_samples: 25
vcf_output:
chrom_style: UCSC
reports:
StemCNV-check-report:
file_type: html
_default_:
include_sections: __all__
exclude_sections: ~
sample.info.extra.cols:
- Chip_Name
- Chip_Pos
CNV_call_labels_removed: Excluded call
call.data.and.plots:
_default_:
min_number_plots: 20
always_include_CNVs: ~
include.plot: yes
include.hotspot.table: yes
include.gene.table.details: Call
plot.flanking.region.relative: 2
plot.region.minsize: 2000000
denovo:
min_number_plots: 20
always_include_CNVs:
- Critical de-novo
- Reportable de-novo
include.plot: yes
include.hotspot.table: yes
include.gene.table.details: Call
plot.flanking.region.relative: 2
plot.region.minsize: 2000000
call_labels_include:
- Critical de-novo
- Reportable de-novo
- de-novo call
reference_gt:
min_number_plots: 20
always_include_CNVs: ~
include.plot: yes
include.hotspot.table: yes
include.gene.table.details: Call
plot.flanking.region.relative: 2
plot.region.minsize: 2000000
call_labels_include: Reference genotype
regions_of_interest:
min_number_plots: 20
always_include_CNVs: ~
include.plot: yes
include.hotspot.table: yes
include.gene.table.details: Call
plot.flanking.region.relative: 2
plot.region.minsize: 100000
SNP_comparison:
dendrogram.color.by: Sample_Group
dendrogram.shape.by: Chip_Name
genome_overview:
call_labels_overview:
- Critical de-novo
- Reportable de-novo
- de-novo call
- Reference genotype
show_reference: yes
wildcard_constraints:
sample_id: '[a-zA-Z0-9-_]+'
sentrix_pos: R[0-9]{2}C[0-9]{2}
sentrix_name: '[0-9]+'
tools:
_default_:
threads: 1
memory: 6000
runtime: 2h
partition: medium
GenCall:
threads: 4
memory: 8000
runtime: 4h
CBS:
memory: 6000
runtime: 1h
CNV.process:
memory: 6000
runtime: 1h
PennCNV:
memory: 4000
runtime: 1h
SNV_analysis:
threads: 2
memory: 20000
runtime: 4h
knitr:
memory: 25000
runtime: 1h
gtc2vcf:
memory: 6000
sample_table: sample_table_reports.xlsx
column_remove_regex: None
basedir: /data/cephfs-1/work/projects/stachelscheid-cellline-arrays/manusscript_2024
configfile: config_reports.yaml
target: complete
cache_path: /data/cephfs-1/home/users/vonkunic_c/work/.stem-cnv-check
verbose_level: 0
is_wsl: 0
snakedir: /data/cephfs-1/work/groups/cubi/users/vonkunic_c/git-repos/StemCNV-check/src/stemcnv_check
report_settings:
include_sections: __all__
exclude_sections: ~
sample.info.extra.cols:
- Chip_Name
- Chip_Pos
CNV_call_labels_removed: Excluded call
call.data.and.plots:
_default_:
min_number_plots: 20
always_include_CNVs: ~
include.plot: yes
include.hotspot.table: yes
include.gene.table.details: Call
plot.flanking.region.relative: 2
plot.region.minsize: 2000000
denovo:
min_number_plots: 20
always_include_CNVs:
- Critical de-novo
- Reportable de-novo
include.plot: yes
include.hotspot.table: yes
include.gene.table.details: Call
plot.flanking.region.relative: 2
plot.region.minsize: 2000000
call_labels_include:
- Critical de-novo
- Reportable de-novo
- de-novo call
reference_gt:
min_number_plots: 20
always_include_CNVs: ~
include.plot: yes
include.hotspot.table: yes
include.gene.table.details: Call
plot.flanking.region.relative: 2
plot.region.minsize: 2000000
call_labels_include: Reference genotype
regions_of_interest:
min_number_plots: 20
always_include_CNVs: ~
include.plot: yes
include.hotspot.table: yes
include.gene.table.details: Call
plot.flanking.region.relative: 2
plot.region.minsize: 100000
SNP_comparison:
dendrogram.color.by: Sample_Group
dendrogram.shape.by: Chip_Name
genome_overview:
call_labels_overview:
- Critical de-novo
- Reportable de-novo
- de-novo call
- Reference genotype
show_reference: yes
file_type: html
R session info
## ─ Session info ───────────────────────────────────────────────────────────────
## setting value
## version R version 4.3.3 (2024-02-29)
## os Rocky Linux 9.6 (Blue Onyx)
## system x86_64, linux-gnu
## ui X11
## language (EN)
## collate C.UTF-8
## ctype C.UTF-8
## tz Europe/Berlin
## date 2025-09-19
## pandoc 3.6.4 @ /data/cephfs-1/home/users/vonkunic_c/work/.stem-cnv-check/f4f9fb2443eadf59b8a94b12a19c1c0f_/bin/ (via rmarkdown)
## quarto NA
##
## ─ Packages ───────────────────────────────────────────────────────────────────
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##
## [1] /data/cephfs-1/work/groups/cubi/users/vonkunic_c/.stem-cnv-check/f4f9fb2443eadf59b8a94b12a19c1c0f_/lib/R/library
## * ── Packages attached to the search path.
##
## ──────────────────────────────────────────────────────────────────────────────CNV calling
de-novo CNV calls
de-novo CNV calls table
⇩
This section describes all de-novo CNV calls, meaning calls without a match in the reference sample. The table allows sorting and filtering the calls by various criteria, default is sorting by Check-Score. The Check-Score is described on our upcoming manuscript and combines contributions from CNV size and copynumber as well as additions from annotation from overlapping stem cell hotspots, cancer driver genes, predicted dosage sensitive genes and other gene annotations.
Hovering over the column headers gives explanations for each column and the “Column visibility” button can be used to change the default selection of visible columns.
The section immediately below the table contains details for each CNV call, including a plot of the CNV region, (if relevant) a table of annotated genes and hotspots, and a table of all genes overlapping the CNV (or plot region).
nr1-cbs_dup_chr2_47806765_47900182
nr2-combined-call_loss_chr22_33707202_33849413
nr3-combined-call_loss_chr13_32042832_32157759
nr4-cbs_del_chr7_49866430_49971392
nr5-cbs_dup_chr19_47042461_47065746
nr6-cbs_del_chr4_69273240_69294494
nr7-penncnv_del_chr11_25680755_25743637
nr8-cbs_del_chr11_14769567_14830944
nr9-cbs_dup_chr12_7609671_7651050
nr10-cbs_dup_chr9_93126535_93163919
nr11-cbs_del_chrx_131100759_131140251
## No genes in the call area.nr12-cbs_del_chrx_45296827_45334004
nr13-cbs_del_chrx_32319433_32353128
nr14-cbs_del_chr4_145387726_145422391
## No genes in the call area.nr15-cbs_del_chr11_87974459_88006065
nr16-cbs_del_chr2_153683688_153713500
## No genes in the call area.nr17-cbs_del_chr7_6074927_6103247
nr18-combined-call_loss_chr5_17483817_17509779
nr19-penncnv_dup_chr3_127068021_127087392
## No genes in the call area.nr20-cbs_dup_chr2_197308812_197323059
Reference genotype CNV calls
reference genotype CNV calls table
⇩
This section describes all reference CNV calls, meaning calls for which a match in the reference sample was found. Matching of CNV calls is based on a minimum of at least 50% reciprocal overlap between sample and reference. Otherwise this section uses the same layout as to the de-novo calls section.
nr1-combined-call_loss_chr16_63870714_64297219
nr2-combined-call_loss_chr1_196743486_196852356
nr3-combined-call_loss_chr3_4069115_4171652
nr4-penncnv_loh_chr5_121811523_122297372
nr5-cbs_dup_chr3_127019606_127166972
nr6-penncnv_loh_chr6_149889403_150249731
nr7-penncnv_loh_chr16_76238719_76652989
nr8-penncnv_loh_chr18_60266934_60681794
nr9-penncnv_loh_chr10_130378643_130789730
nr10-penncnv_loh_chr2_37504234_37877670
nr11-penncnv_loh_chr6_32530203_32817006
nr12-cbs_dup_chr10_133534395_133620799
nr13-penncnv_loh_chr10_133463341_133620799
nr14-penncnv_loh_chr6_31316549_31459190
nr15-cbs_del_chr6_141752404_141798326
## No genes in the call area.nr16-combined-call_loss_chr13_37496412_37540475
nr17-cbs_del_chr11_7793392_7825582
nr18-combined-call_loss_chr10_55204437_55228596
nr19-cbs_del_chr11_25680755_25705515
## No genes in the call area.nr20-penncnv_del_chr6_141752404_141774564
## No genes in the call area.SNV analysis
Table of de-novo SNVs
SNV table explanations
⇩
This table lists all SNVs detected by the Chip Array which are different from the reference genome and are annotated as at least protein changing. Due to their potential impact these are now called “SNVs” rather than “SNPs”, independent of their actual (unknown) frequency in the population.
All SNVs are categorised into one of the following categories (shown in the hidden SNV category column):
ROI-overlap: SNV overlapping a sample specific regions of interest
hotspot-match: SNV matching a known stemcell hotspot mutation (see also SNV hotspot coverage)
hotspot-gene: SNV in a gene with known iPSC hotspots (see also SNV hotspot coverage)
protein-ablation: SNV (likely) fully disrupting protein function (i.e. frameshift, stop gain, stop loss)
protein-changing: SNV causing a change the protein sequence (i.e. missense, inframe)
other: SNV with other unclear or undetermined effect on protein function
The “SNV label” further categorizes the SNVs into:
Critical de-novo: SNV with likely critical significance on hiPSC line
Reportable de-novo: SNV with possible significance on hiPSC line
Unreliable critical/reportable: SNV with likely or possible significance on hiPSC line, but unreliable signal
de-novo SNV: SNV with de-novo status, but no clear functional impact
Reference genotype: SNV already detected in the reference sample
The following categories are assinged as “Critical” or “Reportable” (de-novo):
Critical de-novo: hotspot-match
Reportable de-novo: ROI-overlap
Reportable de-novo: hotspot-gene
Reportable de-novo: protein-ablation
A complete, up-to-date list of all stem cell SNV hotspots is also available online.
The table allows sorting and filtering the SNVs by various criteria, default is sorting by theSNV Label.Hovering over the
column headers gives explanations for each column and the “Column
visibility” button can beused to show (or hide) columns. Each SNV
genotype (GT) is shown in vcf format: each allele is represented by a
single number, separated by a forward slash. A 0 indicates the reference
allele, a 1 indicates the alternate allele. A dot (.) indicates that the
genotype could not be determined.
Table of reference SNVs
SNV hotspot coverage
SNV hotspot coverage explanations
⇩
This table lists all genes that have known point mutation hotspots for stem cells, a source for the hotspots, the selected primary transcript for each gene, as well as the coverage of the genes on cDNA, CDS and protein level (percent coverage of bases/amino acids, as well as absolute numbers). The coverage is based on all probes contained on the utilised array.
The “Hotspots” column, lists the specific annotated protein changes for each gene and whether or not any probe on the array covers each of the specific mutations.SNV QC details
Sample comparison
Genome Overview
Genome overview explanations
⇩
The following plots each show a whole chromosome overview of the sample, combining to a whole genome view. CNV calls (filtered based on the config settings) are shown as colored background bars, with the color indicating the type of call: green for gains, red for losses, and grey for LOH. Additionally, if the sample has a reference, SNVs that are labelled critical or protein changing/unreliable critical are also highlighted in red and orange, respectively.
chr1
chr2
chr3
chr4
chr5
chr6
chr7
chr8
chr9
chr10
chr11
chr12
chr13
chr14
chr15
chr16
chr17
chr18
chr19
chr20
chr21
chr22
chrX
chrY
Identity comparison
Dendrogram explanations
⇩
Sample identities can be comparsed based on the dendrogram built on the SNP genotypes. The dendrogram is built using the manhattan distance between samples, counting both alleles from Probes that are not quality in every included sample. Accordingly, the distance between two samples is the sum of the absolute differences between the two alleles at each SNP (also shown in the table below) after QC filters. Samples that are very close together are likely identical or clonally related. Sample selection as well as color and shape lables are controlled by the config file.
Only 15 shapes are available, but “Chip_Name” would need 17. Consider using fewer unqiue entries. These values are summarised as “Other”: 208305080104, 209362520148
